90% of the 1.5 million Americans living with idiopathic Parkinson's disease (PD) and 50% of the 500,000 Americans living with Multiple Sclerosis (MS) will experience dysarthria. Dysarthria has devastating consequences for life quality and participation in society due to its effects on employment, leisure activities and social relationships. Knowledge of therapy techniques for maximizing perceived speech adequacy, as indexed by the gold standard perceptual construct of intelligibility is thus of vital importance. Owing to the scarcity of impartial comparative studies, the choice of one technique over others is often based on trial and error or reflects clinician bias, both of which are at odds with evidence-based practice. This project has sought to address this critical gap in knowledge regarding the comparative merits of dysarthria treatment techniques since its inception. Toward this end, published studies from the past funding cycle compared the acoustic and perceptual merits of three common, global dysarthria treatment techniques including 1) rate manipulation, 2) an increased vocal intensity and 3) clear speech in MS and PD as well as age and sex matched neurotypical talkers. Global treatment techniques by their very nature elicit co-occurring acoustic changes (e.g., duration, segmental articulation). Because an explanatory, acoustically-based model of intelligibility is lacking, the acoustic change(s) causing or explainin the improved perceptual outcomes of global treatment techniques are unknown. Determining the acoustic variables explaining intelligibility variation in dysarthria would not only tremendousy advance theoretical understanding of intelligibility but also would strengthen the scientific basis for treatment. Treatment focused on those acoustic variables explanatory for improved intelligibility may further accelerate progress in therapy. Importantly, research from the previous funding cycle suggests the promise of speech analysis-resynthesis for identifying segmental and suprasegmental acoustic variables explanatory for intelligibility in dysarthria. Building upon this work, the overarching goal of the continuation is to contribute towards development of an acoustically-based explanatory model of intelligibility. Our approach 1) employs established perceptual procedures and acoustic measures, 2) uses an innovative analysis-resynthesis technique that permits conclusions concerning the explanatory relationship between acoustic changes accompanying dysarthria therapy techniques and intelligibility, and 3) leverages methods from machine learning to build a predictive model of intelligibility from acoustics. The impact of this work is in its contribution to 1) advancing conceptual understanding of intelligibility, 2) strengthening the scientific basis for treatment, and 3) optimizing clinical implementation of dysarthria therapy techniques.